Gauges, for example, speedometer gauges, are commonly used to indicate the speed of moving and/or rotating objects. A typical application for a speedometer gauge is in an automobile where it is used to indicate the speed of the automobile. The speedometer determines the speed of the automobile using wheel sensors which indicate the number of revolutions of the wheel. Since the circumference of the wheel is usually a known, fixed parameter (assuming that original equipment tires or their size equivalent are being used, and that they are properly inflated) the frequency of the wheel sensor signals which normally represent revolutions per unit time interval, can be converted to indicate distance travelled per unit time interval, i.e., speed or velocity.
For example, in the case of an automobile wheel with a circumference of six feet which rotates eight times per second, the wheel speed is:
(6 feet/rotation).(8 rotations/second).(3600 seconds/hour).(1 mile/5280 feet)=32.7 miles hour
On a deflection--type or analog gauge, this signal is converted to an equivalent mechanical force (using a motor) which is applied to a needle in order to deflect the needle the angular distance corresponding to the equivalent wheel speed, as indicated by the circumferential speed markings placed around the periphery of the speedometer gauge.
Gauges, for example, speedometer gauges or instrument clusters, such as those used in automobiles are typically mass produced using a number of individual components, e.g., wheel sensors, needles, and motors. These components typically have variations from part to part and from lot to lot, with the result being that the finished speedometer gauges vary in performance. In other words, a given speed will be displayed differently on different speedometer gauges due to the component variation. This situation is extremely undesirable for such a sensitive instrument whose accuracy is relied upon for safety reasons, performance reasons and of course, legal reasons. Accordingly, it is necessary to test a statistically significant number of speedometer gauges manufactured in order to determine their accuracy. Based on this accuracy testing, only those speedometer gauges exhibiting sufficient accuracy within a given tolerance (e.g., 1-2 miles per hour) will be retained. The remaining speedometer gauges are rejected as being inaccurate.
The foregoing accuracy test may be carded out by applying a known input signal to the speedometer gauge to simulate a known wheel velocity, and visually observing the output of the speedometer, i.e., the speed indicated by the speedometer gauge. Although such an approach is very effective, it is nevertheless extremely tedious and time consuming. As with other tedious and time consuming tasks which happen to be repetitive in nature, such a task lends itself to automation. However, when using automated techniques, the visual assessment made by an operator must now be made by a machine, i.e., the speed indicated by the speedometer gauge must be "read" and a determination made as to whether or not the particular speedometer is within the acceptable range of accuracy.
Visual inspection or object identification systems are often used for similar tasks. For example, U.S. Pat. No. 4,581,762 to Lapidus et at. discloses an automated object identification system which compares unknown objects to a known reference object. The comparison or identification includes selecting three points on the known object and calculating the gradient information around each point. Each of the three areas of gradient information is compared to an image of the known object. If "good" correlation is found in the image of the unknown object, then the unknown object has been identified as matching the known object. Additionally, the angular displacement of the three points on the unknown object is used to determine the orientation of the unknown object.
Similarly, U.S. Pat. No. 5,077,806 to Peters et at. discloses an object identification system used to identify a particular object by producing an image of the object and then counting the number of "on" pixels in each line of the image. This characteristic information is then used to identify the particular object.
Although the above-described systems may be used to visually identify objects, they are not readily applicable to the visual assessment of the performance and accuracy of mass produced gauges. Peters et at. merely identify an object and provide no information whatsoever that can be used to visually assess a speedometer gauge. Although Lapidus et at. may be used to determine angular displacement of a speedometer, such a system is extremely complex and computation-intensive in that it requires a detailed calculation of several gradients. Furthermore, this latter system requires elaborate illumination techniques used for edge detection.